A recent report from the European VISCONTI group estimated that 14-15% of patients treated very early during infection were able to discontinue therapy and maintain viral suppression for several years without any therapy. This estimate of 15% is much higher than expected and requires confirmation. Since then, no other group has been able to confirm or refute this finding, most likely because very large numbers of individuals are required to find enough patients eligible for evaluation for PTC, since most patients on suppressive therapy rarely discontinue treatment. Therefore, in order to get a large enough sample size to definitively estimate the prevalence of PTC and associated factors associated with PTC it is necessary to combine data from similar but independent sources conducting research on acute and very early HIV infection. The primary goal of this project is to combine data in a standardized manner from three sources: The historical Acute Infection/Early Disease Research Program (AIEDRP) database, the University of Washington Primary Infection Cohort database and the University of California San Diego Primary Infection Cohort database. This combined database will be referred to as to the PTC Database and will be used to obtain a preliminary estimate of the percentage of PTCs in combination from the three sources, improving on the estimates that have been obtained by both the UW and UCSD groups independently. In addition, a formal protocol, based on procedures for QC and formatting identified while combining these three data sets, will be developed. This protocol will provide specific instructions on how to QC and format data for inclusion in the PTC Database. Once we establish feasibility for combing data sets with the information needed to estimate the prevalence of PTC and develop a protocol with instructions on how to prepare datasets for inclusion in the PTC Database, an R01 application is planned which will recruit additional sites to contribute data to the PTC Database. The protocol will be provided to each site so that they can prepare their individual data sets efficiently and consistently to be included in the PTC Database. This database would then be used to estimate the prevalence of PTCs and evaluate correlates and other mechanisms of PTC. Information on predictors and other features of PTCs may allow certain patients with those predictors and features to consider a treatment interruption. In addition, the identification of factors associated with PTCs could direct additionl research on finding a functional cure for HIV.